Modifications in the Topological Structure of EEG Functional Connectivity Networks during Listening Tonal and Atonal Concert Music in Musicians and Non-Musicians

The present work aims to demonstrate the hypothesis that atonal music modifies the topological structure of electroencephalographic (EEG) connectivity networks in relation to tonal music. To this, EEG monopolar records were taken in musicians and non-musicians while listening to tonal, atonal, and pink noise sound excerpts. EEG functional connectivities (FC) among channels assessed by a phase synchronization index previously thresholded using surrogate data test were computed. Sound effects, on the topological structure of graph-based networks assembled with the EEG-FCs at different frequency-bands, were analyzed throughout graph metric and network-based statistic (NBS). Local and global efficiency normalized (vs. random-network) measurements (NLE|NGE) assessing network information exchanges were able to discriminate both music styles irrespective of groups and frequency-bands. During tonal audition, NLE and NGE values in the beta-band network get close to that of a small-world network, while during atonal and even more during noise its structure moved away from small-world. These effects were attributed to the different timbre characteristics (sounds spectral centroid and entropy) and different musical structure. Results from networks topographic maps for strength and NLE of the nodes, and for FC subnets obtained from the NBS, allowed discriminating the musical styles and verifying the different strength, NLE, and FC of musicians compared to non-musicians.

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SYNCHRONIZATION BEHAVIOR IN DISCRETE SYSTEMS

International Journal of Modern Physics C ◽

10.1142/s012918311101635x ◽

2011 ◽

Vol 22 (05) ◽

pp. 441-448

Author(s):

JIAN-FENG ZHENG ◽

ZI-YOU GAO ◽

LING-XIAO YANG ◽

BAI-BAI FU

Keyword(s):

Network Structure ◽

Phase Synchronization ◽

Random Network ◽

Small World ◽

Discrete Systems ◽

Discrete State ◽

Scale Free ◽

State Transfer ◽

Free Network ◽

The Impact

This work explores the synchronization behavior in discrete systems with both discrete time and discrete state. In order to describe the self-driven function of the node’s state, a state transfer matrix is introduced. Three typical network structures (random network, small-world network and scale-free network) are numerically studied in order to investigate the impact of network structure. Simulation results show that, according to the phase synchronization index, the coupling strength is divided into four regions: the increasing region, the maximum region, the decreasing region and the oscillation region. Moreover, the size of the oscillation region seems to be changeless, independent of the network structure and a parameter describing the number of total node’s states.

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Sublinear domination and core–periphery networks

Scientific Reports ◽

10.1038/s41598-021-94105-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Marios Papachristou

Keyword(s):

Network Model ◽

Power Law ◽

Real World ◽

Random Network ◽

Small World ◽

The Core ◽

Entire Network

AbstractIn this paper we devise a generative random network model with core–periphery properties whose core nodes act as sublinear dominators, that is, if the network has n nodes, the core has size o(n) and dominates the entire network. We show that instances generated by this model exhibit power law degree distributions, and incorporates small-world phenomena. We also fit our model in a variety of real-world networks.

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Analysis on Invulnerability of Wireless Sensor Network towards Cascading Failures Based on Coupled Map Lattice

Complexity ◽

10.1155/2018/6386324 ◽

2018 ◽

Vol 2018 ◽

pp. 1-14 ◽

Cited By ~ 4

Author(s):

Xiuwen Fu ◽

Yongsheng Yang ◽

Haiqing Yao

Keyword(s):

Random Network ◽

Small World ◽

Coupled Map Lattice ◽

Wireless Sensor ◽

Cascading Failures ◽

Scale Free Network ◽

Scale Free ◽

Network Topologies ◽

Free Network ◽

Entire Network

Previous research of wireless sensor networks (WSNs) invulnerability mainly focuses on the static topology, while ignoring the cascading process of the network caused by the dynamic changes of load. Therefore, given the realistic features of WSNs, in this paper we research the invulnerability of WSNs with respect to cascading failures based on the coupled map lattice (CML). The invulnerability and the cascading process of four types of network topologies (i.e., random network, small-world network, homogenous scale-free network, and heterogeneous scale-free network) under various attack schemes (i.e., random attack, max-degree attack, and max-status attack) are investigated, respectively. The simulation results demonstrate that the rise of interference R and coupling coefficient ε will increase the risks of cascading failures. Cascading threshold values Rc and εc exist, where cascading failures will spread to the entire network when R>Rc or ε>εc. When facing a random attack or max-status attack, the network with higher heterogeneity tends to have a stronger invulnerability towards cascading failures. Conversely, when facing a max-degree attack, the network with higher uniformity tends to have a better performance. Besides that, we have also proved that the spreading speed of cascading failures is inversely proportional to the average path length of the network and the increase of average degree k can improve the network invulnerability.

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Hyperbrain features of team mental models within a juggling paradigm: a proof of concept

PeerJ ◽

10.7717/peerj.2457 ◽

2016 ◽

Vol 4 ◽

pp. e2457 ◽

Cited By ~ 15

Author(s):

Edson Filho ◽

Maurizio Bertollo ◽

Gabriella Tamburro ◽

Lorenzo Schinaia ◽

Jonas Chatel-Goldman ◽

...

Keyword(s):

Mental Models ◽

Task Difficulty ◽

Functional Organization ◽

Cooperative Behavior ◽

Motor Task ◽

Small World ◽

Proof Of Concept ◽

Frequency Bands ◽

Functional Connections ◽

Graph Metrics

BackgroundResearch on cooperative behavior and the social brain exists, but little research has focused on real-time motor cooperative behavior and its neural correlates. In this proof of concept study, we explored the conceptual notion of shared and complementary mental models through EEG mapping of two brains performing a real-world interactive motor task of increasing difficulty. We used the recently introduced participative “juggling paradigm,” and collected neuro-physiological and psycho-social data. We were interested in analyzing the between-brains coupling during a dyadic juggling task, and in exploring the relationship between the motor task execution, the jugglers’skill level and the task difficulty. We also investigated how this relationship could be mirrored in the coupled functional organization of the interacting brains.MethodsTo capture the neural schemas underlying the notion of shared and complementary mental models, we examined the functional connectivity patterns and hyperbrain features of a juggling dyad involved in cooperative motor tasks of increasing difficulty. Jugglers’ cortical activity was measured using two synchronized 32-channel EEG systems during dyadic juggling performed with 3, 4, 5 and 6 balls. Individual and hyperbrain functional connections were quantified through coherence maps calculated across all electrode pairs in the theta and alpha bands (4–8 and 8–12 Hz). Graph metrics were used to typify the global topology and efficiency of the functional networks for the four difficulty levels in the theta and alpha bands.ResultsResults indicated that, as task difficulty increased, the cortical functional organization of the more skilled juggler became progressively more segregated in both frequency bands, with a small-world organization in the theta band during easier tasks, indicative of a flow-like state in line with the neural efficiency hypothesis. Conversely, more integrated functional patterns were observed for the less skilled juggler in both frequency bands, possibly related to cognitive overload due to the difficulty of the task at hand (reinvestment hypothesis). At the hyperbrain level, a segregated functional organization involving areas of the visuo-attentional networks of both jugglers was observed in both frequency bands and for the easier task only.DiscussionThese results suggest that cooperative juggling is supported by integrated activity of specialized cortical areas from both brains only during easier tasks, whereas it relies on individual skills, mirrored in uncorrelated individual brain activations, during more difficult tasks. These findings suggest that task difficulty and jugglers’ personal skills may influence the features of the hyperbrain network in its shared/integrative and complementary/segregative tendencies.

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No changes in parieto-occipital alpha during neural phase locking to visual quasi-periodic theta-, alpha-, and beta-band stimulation

10.1101/219766 ◽

2017 ◽

Cited By ~ 2

Author(s):

Christian Keitel ◽

Christopher SY Benwell ◽

Gregor Thut ◽

Joachim Gross

Keyword(s):

Alpha Rhythm ◽

Visual Stimulation ◽

Phase Locking ◽

Stimulation Frequency ◽

Alpha Band ◽

Human Visual Perception ◽

Beta Band ◽

Frequency Bands ◽

Low Intensity ◽

Increased Sensitivity

ABSTRACTRecent studies have probed the role of the parieto-occipital alpha rhythm (8 – 12 Hz) in human visual perception through attempts to drive its neural generators. To that end, paradigms have used high-intensity strictly-periodic visual stimulation that created strong predictions about future stimulus occurrences and repeatedly demonstrated perceptual consequences in line with an entrainment of parieto-occipital alpha. Our study, in turn, examined the case of alpha entrainment by non-predictive low-intensity quasi-periodic visual stimulation within theta-(4 – 7 Hz), alpha-(8 – 13 Hz) and beta (14 – 20 Hz) frequency bands, i.e. a class of stimuli that resemble the temporal characteristics of naturally occurring visual input more closely. We have previously reported substantial neural phase-locking in EEG recording during all three stimulation conditions. Here, we studied to what extent this phase-locking reflected an entrainment of intrinsic alpha rhythms in the same dataset. Specifically, we tested whether quasi-periodic visual stimulation affected several properties of parieto-occipital alpha generators. Speaking against an entrainment of intrinsic alpha rhythms by non-predictive low-intensity quasi-periodic visual stimulation, we found none of these properties to show differences between stimulation frequency bands. In particular, alpha band generators did not show increased sensitivity to alpha band stimulation and Bayesian inference corroborated evidence against an influence of stimulation frequency. Our results set boundary conditions for when and how to expect effects of entrainment of alpha generators and suggest that the parieto-occipital alpha rhythm may be more inert to external influences than previously thought.

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Decoding the Musical Message via the Structural Analogy between Verbal and Musical Language

Artes Journal of Musicology ◽

10.2478/ajm-2018-0009 ◽

2018 ◽

Vol 18 (1) ◽

pp. 151-160

Author(s):

Rosina Caterina Filimon

Keyword(s):

Cognitive Psychology ◽

Musical Structure ◽

Musical Language ◽

Tonal Music ◽

Verbal Language ◽

Musical Perception ◽

Language And Music ◽

Structural Analogy ◽

Human Intellect ◽

Universal Nature

Abstract The topic approached in this paper aims to identify the structural similarities between the verbal and the musical language and to highlight the process of decoding the musical message through the structural analogy between them. The process of musical perception and musical decoding involves physiological, psychological and aesthetic phenomena. Besides receiving the sound waves, it implies complex cognitive processes being activated, whose aim is to decode the musical material at cerebral level. Starting from the research methods in cognitive psychology, music researchers redefine the process of musical perception in a series of papers in musical cognitive psychology. In the case of the analogy between language and music, deciphering the musical structure and its perception are due, according to researchers, to several common structural configurations. A significant model for the description of the musical structure is Noam Chomsky’s generative-transformational model. This claimed that, at a deep level, all languages have the same syntactic structure, on account of innate anatomical and physiological structures which became specialized as a consequence of the universal nature of certain mechanisms of the human intellect. Chomsky’s studies supported by sophisticated experimental devices, computerised analyses and algorithmic models have identified the syntax of the musical message, as well as the rules and principles that underlie the processing of sound-related information by the listener; this syntax, principles and rules show surprising similarities with the verbal language. The musicologist Heinrich Schenker, 20 years ahead of Chomsky, considers that there is a parallel between the analysis of natural language and that of the musical structure, and has developed his own theory on the structure of music. Schenker’s structural analysis is based on the idea that tonal music is organized hierarchically, in a layering of structural levels. Thus, spoken language and music are governed by common rules: phonology, syntax and semantics. Fred Lerdahl and Ray Jackendoff develop a musical grammar where a set of generating rules are defined to explain the hierarchical structure of tonal music. The authors of the generative theory propose the hypothesis of a musical grammar based on two types of rules, which take into account the conscious and unconscious principles that govern the organization of the musical perception. The structural analogy between verbal and musical language consists of several common elements. Among those is the hierarchical organization of both fields, a governance by the same rules – phonology, syntax, semantics – and as a consequence of the universal nature of certain mechanisms of the human intellect, decoding the transmitted message is accomplished thanks to some universal innate structures, biologically inherited. Also, according to Chomsky's linguistics model a musical grammar is configured, one governed by wellformed rules and preference rules. Thus, a musical piece is not perceived as a stream of disordered sounds, but it is deconstructed, developed and assimilated at cerebral level by means of cognitive pre-existing schemes.

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Factor or Network Model? Predictions From Neural Networks

Journal of Behavioral Data Science ◽

10.35566/jbds/v1n1/p5 ◽

2021 ◽

Vol 1 (1) ◽

Author(s):

Alexander P. Christensen ◽

Keyword(s):

Neural Networks ◽

Network Model ◽

Latent Variable ◽

Random Network ◽

Network Models ◽

Small World ◽

Small World Network ◽

Monte Carlo Simulation Study ◽

Psychological Phenomena ◽

The Neural Networks

The nature of associations between variables is important for constructing theory about psychological phenomena. In the last decade, this topic has received renewed interest with the introduction of psychometric network models. In psychology, network models are often contrasted with latent variable (e.g., factor) models. Recent research has shown that differences between the two tend to be more substantive than statistical. One recently developed algorithm called the Loadings Comparison Test (LCT) was developed to predict whether data were generated from a factor or small-world network model. A significant limitation of the current LCT implementation is that it's based on heuristics that were derived from descriptive statistics. In the present study, we used artificial neural networks to replace these heuristics and develop a more robust and generalizable algorithm. We performed a Monte Carlo simulation study that compared neural networks to the original LCT algorithm as well as logistic regression models that were trained on the same data. We found that the neural networks performed as well as or better than both methods for predicting whether data were generated from a factor, small-world network, or random network model. Although the neural networks were trained on small-world networks, we show that they can reliably predict the data-generating model of random networks, demonstrating generalizability beyond the trained data. We echo the call for more formal theories about the relations between variables and discuss the role of the LCT in this process.

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Abstract 17426: Pulmonary Vein Isolation ‘Rewires’ Electrical Communications to Enhance Small-world Network Topology During Atrial Fibrillation

Circulation ◽

10.1161/circ.132.suppl_3.17426 ◽

2015 ◽

Vol 132 (suppl_3) ◽

Author(s):

Hiroshi Ashikaga ◽

Jonathan Chrispin ◽

Degang Wu ◽

Joshua Garland

Keyword(s):

Atrial Fibrillation ◽

Communication Network ◽

Mutual Information ◽

Path Length ◽

Random Network ◽

Small World ◽

Clustering Coefficient ◽

Small World Network ◽

Z Score ◽

Network Properties

Recent evidence suggests that pulmonary vein isolation (PVI) may perturb the electrophysiological substrate for maintenance of atrial fibrillation (AF). Our previous work indicates that information theory metrics can quantify electrical communications during arrhythmia. We hypothesized that PVI ‘rewires’ the electrical communication network during AF such that the topology exhibits higher levels of small-world network properties, with higher clustering coefficient and lower path length, than would be expected by chance. Thirteen consecutive patients (n=6 with prior PVI and n=7 without) underwent AF ablation using a 64-electrode basket catheter in the left atrium. Multielectrode recording was performed during AF for 60 seconds, followed by PVI. Mutual information was calculated from the time series between each pair of electrodes using the Kraskov-Stögbauer-Grassberger estimator. The all-to-all mutual information matrix (64x64; Figure, upper panels) was thresholded by the median and standard deviations of mutual information to build a binary adjacency matrix for electrical communication networks. The properties of small-world network ( swn ; ‘small-world-ness’) were quantified by the ratio of the observed average clustering coefficient to that of a random network over the ratio of the observed average path length to that of a random network. swn was expressed in normal Z standard deviation units. As the binarizing threshold increased, the Z-score of swn decreased (Figure, lower panel). However, the Z-score at each threshold value was consistently higher with prior PVI than those without (p<0.05). In conclusion, electrical communication network during AF with prior PVI is associated with higher levels of small-world network properties than those without. This finding supports the concept that PVI perturbs the underlying substrate. In addition, swn of electrical communication network may be a promising metric to quantify substrate modification.

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Adaptive Peer-to-Peer Social Networks for Distributed Content-Based Web Search

Virtual Communities ◽

10.4018/978-1-60960-100-3.ch307 ◽

2011 ◽

pp. 762-784 ◽

Cited By ~ 1

Author(s):

Le-Shin Wu ◽

Ruj Akavipat ◽

Ana Gabriela Maguitman ◽

Filippo Menczer

Keyword(s):

Search Engines ◽

Web Search ◽

Random Network ◽

Routing Algorithm ◽

Small World ◽

Query Routing ◽

Learning Techniques ◽

Peer Network ◽

User Communities

This chapter proposed a collaborative peer network application called 6Search (6S) to address the scalability limitations of centralized search engines. Each peer crawls the Web in a focused way, guided by its user’s information context. Through this approach, better (distributed) coverage can be achieved. Each peer also acts as a search “servent” (server + client) by submitting and responding to queries to/from its neighbors. This search process has no centralized bottleneck. Peers depend on a local adaptive routing algorithm to dynamically change the topology of the peer network and search for the best neighbors to answer their queries. We present and evaluate learning techniques to improve local query routing. We validate prototypes of the 6S network via simulations with model users based on actual Web crawls. We find that the network topology rapidly converges from a random network to a small world network, with clusters emerging from user communities with shared interests. We finally compare the quality of the results with those obtained by centralized search engines such as Google.

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